Triple
T17644285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMART bus network |
E429315
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | SMART |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: SMART | Statement: [SMART bus network, shortName, SMART]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SMART Context triple: [SMART bus network, shortName, SMART]
-
A.
SMART
SMART is a commuter rail service operating in California’s Sonoma and Marin counties, providing passenger transportation along the North Bay corridor.
-
B.
SMART
chosen
SMART (South Metro Area Regional Transit) is a public transportation agency serving the southern Portland metropolitan area in Oregon with bus and transit services.
-
C.
SMART
SMART is the primary public bus transit system serving the suburban communities of the Detroit metropolitan area in Michigan.
-
D.
Smart
Smart is a surname most prominently associated in sports with Shaka Smart, a successful American college basketball coach.
-
E.
smart
smart is an automotive marque best known for its compact city cars and microcars, originally developed in partnership with Swatch and later owned by Mercedes-Benz.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46de7da4881908d67f447910dba2f |
completed | April 19, 2026, 5:53 a.m. |
Created at: April 10, 2026, 6:04 a.m.